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An Empirical and Doctrinal Analysis of Artificial Intelligence Utilization Among Juris Doctor Students in Zamboanga City, Philippines

Author

Listed:
  • Rivero III, Roberto
  • Atilano, Lesley Ann
  • Moreno, Frede

Abstract

This study investigates the utilization of artificial intelligence (AI) among Juris Doctor (JD) students in Zamboanga City, Philippines, combining empirical and doctrinal analysis. The research employs a mixed-methods approach, synthesizing data from surveys (N=150), interviews, and focus group discussions, alongside doctrinal review of Philippine legal education norms and professional responsibility standards. Findings indicate that students frequently adopt AI for research, case summarization, drafting, and exam preparation, yet institutional guidance and ethical clarity remain limited. Only 34% of students consistently disclose AI use, and faculty report inconsistent policies across courses. Doctrinal analysis identifies three guiding principles for AI integration: transparency, competence, and alignment with assessment objectives. Applying these principles, the study proposes that law schools develop localized pedagogical frameworks, including AI literacy instruction, disclosure protocols, and assessment strategies that emphasize reasoning processes. The research underscores a regulatory vacuum in Philippine legal education regarding AI, highlighting the need for institution-specific policies to maintain doctrinal rigor, academic integrity, and professional competence. By situating empirical evidence within doctrinal and pedagogical frameworks, the study provides actionable recommendations for responsible AI adoption, contributing to the scholarship on technology integration in legal education in non-metropolitan, Global South contexts.

Suggested Citation

  • Rivero III, Roberto & Atilano, Lesley Ann & Moreno, Frede, 2026. "An Empirical and Doctrinal Analysis of Artificial Intelligence Utilization Among Juris Doctor Students in Zamboanga City, Philippines," MPRA Paper 127613, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:127613
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    File URL: https://mpra.ub.uni-muenchen.de/127613/1/MPRA_paper_127613.pdf
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    References listed on IDEAS

    as
    1. John Zeleznikow, 2021. "Using Artificial Intelligence to provide Intelligent Dispute Resolution Support," Group Decision and Negotiation, Springer, vol. 30(4), pages 789-812, August.
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    More about this item

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    JEL classification:

    • I0 - Health, Education, and Welfare - - General
    • I2 - Health, Education, and Welfare - - Education
    • I20 - Health, Education, and Welfare - - Education - - - General
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • I29 - Health, Education, and Welfare - - Education - - - Other
    • K00 - Law and Economics - - General - - - General (including Data Sources and Description)
    • K10 - Law and Economics - - Basic Areas of Law - - - General (Constitutional Law)
    • K19 - Law and Economics - - Basic Areas of Law - - - Other
    • K30 - Law and Economics - - Other Substantive Areas of Law - - - General
    • Y50 - Miscellaneous Categories - - Further Reading - - - Further Reading
    • Y80 - Miscellaneous Categories - - Related Disciplines - - - Related Disciplines
    • Z0 - Other Special Topics - - General

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